Recognition of Sign Language Based on Hand Gestures

The target of SLR or sign language recognition is to interpret the sign language into text, respectively. So the deaf and mute people can communicate with ordinary people easily. Sign language recognition has a tremendous social impact; however, it is challenging due to the significant variations and complexity in the hand actions. There are many existing methods for recognizing sign language that uses handcraft features for describing the motion of sign language and then, based on the features it makes the classification models. To approach the problem, we have discussed considering the KNN that can conveniently extract the features. The proposed model can be validated on a real data set.

Optical Solutions of Fokas-Lenells Equation via (m-1/G') - Expansion Method

In this research paper, we investigate some novel soliton solutions to the perturbed Fokas-Lenells equation by using the (m + 1/G') expansion method. Some new solutions are obtained and they are plotted in two and three dimensions. This technique appears as a suitable, applicable, and efficient method to search for the exact solutions of nonlinear partial differential equations in a wide range. All gained optical soliton solutions are substituted into the FokasLenells equation and they verify it. The constraint conditions are also given.